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Silvia Fareri

Publications and source records attributed to Silvia Fareri.

3 recordsLinked to original sources

The Energy Worker Profiler from Technologies to Skills to Realize Energy Efficiency in Manufacturing

In recent years, the manufacturing sector has been responsible for nearly 55 percent of total energy consumption, inducing a major impact on the global ecosystem. Although stricter regulations, restrictions on heavy manufacturing and technological advances are increasing its sustainability, zero-emission and fuel-efficient manufacturing is still considered a utopian target. In parallel,companies that have invested in digital innovation now need to align their internal competencies to maximize their return on investment. Moreover, a primary feature of Industry 4.0 is the digitization of production processes, which offers the opportunity to optimize energy consumption. However, given the speed with which innovation manifests itself, tools capable of measuring the impact that technology is having on digital and green professions and skills are still being designed. In light of the above, in this article we present the Worker Profiler, a software designed to map the skills currently possessed by workers, identifying misalignment with those they should ideally possess to meet the renewed demands that digital innovation and environmental preservation impose. The creation of the Worker Profiler consists of two steps: first, the authors inferred the key technologies and skills for the area of interest, isolating those with markedly increasing patent trends and identifying green and digital enabling skills and occupations. Thus, the software was designed and implemented at the user-interface level. The output of the self-assessment is the definition of the missing digital and green skills and the job roles closest to the starting one in terms of current skills; both the results enable the definition of a customized retraining strategy. The tool has shown evidence of being user-friendly, effective in identifying skills gaps and easily adaptable to other contexts.

cs.CL

SkillNER: Mining and Mapping Soft Skills from any Text

In today's digital world, there is an increasing focus on soft skills. On the one hand, they facilitate innovation at companies, but on the other, they are unlikely to be automated soon. Researchers struggle with accurately approaching quantitatively the study of soft skills due to the lack of data-driven methods to retrieve them. This limits the possibility for psychologists and HR managers to understand the relation between humans and digitalisation. This paper presents SkillNER, a novel data-driven method for automatically extracting soft skills from text. It is a named entity recognition (NER) system trained with a support vector machine (SVM) on a corpus of more than 5000 scientific papers. We developed this system by measuring the performance of our approach against different training models and validating the results together with a team of psychologists. Finally, SkillNER was tested in a real-world case study using the job descriptions of ESCO (European Skill/Competence Qualification and Occupation) as textual source. The system enabled the detection of communities of job profiles based on their shared soft skills and communities of soft skills based on their shared job profiles. This case study demonstrates that the tool can automatically retrieve soft skills from a large corpus in an efficient way, proving useful for firms, institutions, and workers. The tool is open and available online to foster quantitative methods for the study of soft skills.

cs.CL

Lights and shadows of COVID-19, Technology and Industry 4.0

Scientific discoveries and technologies played a significant role in the digital revolution that occurred over the last years. But what is their role in the turmoil brought by the current pandemic? The aim of this paper is to show how digital technologies are operating during this first phase of the spreading of COVID-19. The study analyses and debates the current and potential role of digital technologies, focusing on their influence in the industrial and social fields. More specifically we used the blogging platform "Medium", which has seen an exponential growth in its production of articles over the last couple of months. Even if different from esteemed scientific sources, this platform provides a structure that suits our analysis. We searched how many times digital technologies are mentioned in articles regarding Coronavirus and, after collecting these articles, we collected page tags (comparable to "keywords" in scientific articles) and classified them (technology tags and non-technology tags), to create a graph showing the relation between them. This network allowed us to acknowledge and picture how technologies are currently debated. This was the starting point to discuss the key implications for an imminent future, and question about the impact on industry, society and labour market. What are the opportunities or threats of using technologies of Industry 4.0? Which are the needs rising because of the pandemic and how can technologies help in their fulfillment? How will the industrial scenario change after this pandemic? How will the labour market be affected? How can technologies be advantageous in the emerging social challenges?

cs.CY